期刊
NATURE GENETICS
卷 53, 期 5, 页码 638-+出版社
NATURE PORTFOLIO
DOI: 10.1038/s41588-021-00840-z
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资金
- National Institute of Health (NIH) [1DP2HD084069-01]
- Stanford Bio-X Bowes Fellowship
- Stanford School of Medicine Dean's Postdoctoral Fellowship
- Jane Coffin Childs Postdoctoral Fellowship
- NIH/ENCODE [5UM1HG009436-02]
A new statistical method has been developed to robustly identify gene co-essentiality and yield a genome-wide set of functional modules, predicting the functions of 108 uncharacterized genes effectively.
A central question in the post-genomic era is how genes interact to form biological pathways. Measurements of gene dependency across hundreds of cell lines have been used to cluster genes into 'co-essential' pathways, but this approach has been limited by ubiquitous false positives. In the present study, we develop a statistical method that enables robust identification of gene co-essentiality and yields a genome-wide set of functional modules. This atlas recapitulates diverse pathways and protein complexes, and predicts the functions of 108 uncharacterized genes. Validating top predictions, we show that TMEM189 encodes plasmanylethanolamine desaturase, a key enzyme for plasmalogen synthesis. We also show that C15orf57 encodes a protein that binds the AP2 complex, localizes to clathrin-coated pits and enables efficient transferrin uptake. Finally, we provide an interactive webtool for the community to explore our results, which establish co-essentiality profiling as a powerful resource for biological pathway identification and discovery of new gene functions. A new statistical approach to gene co-essentiality mapping identifies a genome-wide set of functional modules. This analysis predicts the functions of 108 uncharacterized genes.
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